Synopses & Reviews
Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits.
Adaptation in Natural and Artificial Systems is the book that initiated this field of study, presenting the theoretical foundations and exploring applications.
In its most familiar form, adaptation is a biological process, whereby organisms evolve by rearranging genetic material to survive in environments confronting them. In this now classic work, Holland presents a mathematical model that allows for the nonlinearity of such complex interactions. He demonstrates the model's universality by applying it to economics, physiological psychology, game theory, and artificial intelligence and then outlines the way in which this approach modifies the traditional views of mathematical genetics.
Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways. Along the way he accounts for major effects of coadaptation and coevolution: the emergence of building blocks, or schemata, that are recombined and passed on to succeeding generations to provide, innovations and improvements.
Review
Read this book, and even if you don't read it, buy it and display it proudly. Scientists, engineers, and coffee tables the world over should be interested in the revised edition of this seminal book that first gathered and developed the critical mass of ideas from mathematics, computational science, and systems theory necessary to launch and fuel the ongoing revolution in complex innovating systems. From mathematical optimization to the immune system, from machine learning to the central nervous system, from automatic control systems to even something as complex as human society itself, all innovating systems fall under the spell of Holland's mathematical-computational magic, and all individuals interested in understanding engineering such systems ignore Holland at their peril. The MIT Press
Review
Adaptation by natural selection has many analogies with adaptive learning to the environment in the higher animals and in human individuals and society. The possibility of exploiting this analogy to solve problems and to model individual and social behavior has become greatly enhanced with the resources of modern computing. John Holland has brilliantly drawn the analogies with precise algorithmic accuracy and has analyzed the different levels of adaptation and their interrelation. His methods have been employed in studying economic interactions and have permitted a replication of the economy in terms of artificial adaptive agents learning new strategies, an approach which permits us to see the effects of varying modes and capacities for adaptation on the workings of the economy. David E. Goldberg, Unviersity of Illinois-Champaign
Review
This book is required reading for anyone who is interested in the evolution of complex adaptive behavior. Kenneth J. Arrow, Stanford University
Review
Adaptation in Natural and Artificial Systems is a classic. It launched the entire field of genetic algorithms and was one of the principal inspiration for the now-blossoming research area of Artificial Life. W. Danny Hillis, Thinking Machines Corporation
Review
The last decade has seen a resurgence of interest in biological inspiration for parallel computing systems: first, the artificial neural networks inspired by study of the brain, and the genetic algorithms inspired by the study of natural selection and evolution. Inevitably, newcomers to the field are beginning to suggest unifications. It will thus come as a delight to many to learn that John Holland's book...created the study of genetic algorithms within exactly such a interdisciplinary perspective. Douglas R. Hofstadter, Indiana University
Review
John Holland is a modern seer. Over fifteen years ago...he conceived a unified framework for adaptation and from that invented the genetic algorithms whose use in engineering, science, and especially, contemporary artificial intelligence and artificial life has -- after a long gestation in which the rest of us caught up -- entered a phase of explosive growth. Michael Arbib, University of Southern California
Review
This book will be enjoyed by all students of population genetics and evolution. The MIT Press has performed a real service by making it available again to a wide audience. Stewart Wilson, Rowland Institute
Synopsis
Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits.
Synopsis
John H. Holland is Professor of Psychology and Professor of Electrical Engineering and Computer Science at the University of Michigan. He is also Maxwell Professor at the Santa Fe Institute and is Director of the University of Michigan/Santa Fe Institute Advanced Research Program.
Description
Includes bibliographical references (p. 203-205) and index.
About the Author
John Holland is Professor of Psychology at the University of Michigan, Ann Arbor.